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Item Cluster Base Network: A Neighborhood Watch Approach(Office of the Vice Chancellor for Research, 2013-04-05) ZareAfifi, Saharnaz; King, BrianSensors can significantly impact one’s life, they can be used to measure various phenomena such as CO2, temperature, chemicals, water quality, etc. They can also be used in surveillance situations. The data collected by the sensors is processed into information from which decisions are made. Faulty information could cause severe problems. For example, a CO2 sensor with a low battery charge may trigger a false CO2 alarm, causing emergency personnel to respond, thus causing a temporary shortage of personnel able to respond to real emergencies. This situation is exacerbated in a sensor network where data collected is highly sensitive and decisions are important. Furthermore, sensor networks are ad-hoc in nature, with no central authority to analyze network behavior. A goal of our research is to construct energy efficient mechanisms that increase the integrity of the data collected within the sensor network in the presence of potential malicious behavior, sensors with weakened battery power, and/or faulty sensors. A mechanism that we have used in our research is a cluster-based approach. Here the ad-hoc network is partitioned into small clusters. Data collection, communications and processing can be observed by cluster members. The cluster members can police each other, assessing the trustworthiness of each member and collectively signing this assessment. Thus sensors can act as neighborhood watch in a large city, in the sense neighbors watch each other's house to protect each other and enhance the security of the neighborhood. In this research, we developed an energy efficient network protocol that constructs clusters without the use of a central authority. We have also constructed an energy efficient protocol for a cluster to assess members’ trustworthiness and mechanisms that allow the cluster to sign this assessment.Item Heuristic Based Sensor Ranking Algorithm for Indoor Tracking Applications(Office of the Vice Chancellor for Research, 2013-04-05) Rybarczyk, Ryan; Raje, Rajeev R.; Tuceryan, MihranLocation awareness in an indoor setup is an important function necessary in many application domains such as asset management, critical care, and augmented reality. Location awareness, or tracking, of an object within an indoor setting requires a high degree of accuracy, as room-to-room location may be very important. With the current proliferation of smart devices, with often a multitude of built-in sensors, and inexpensive sensors it is now possible to build a network of sensors, for the purpose of tracking, within an indoor environment without the high cost of installing the needed tracking infrastructure. In an effort to increase accuracy, as well as coverage area, various different sensors may be used in the tracking of an object. In this heterogeneous tracking situation, it is important for the tracking infrastructure to quickly and accurately decide which, all or a subset, of available sensors to use. Challenges related to heterogeneous data fusion and clock synchronization, must be addressed in order to provide accurate location estimates. We have proposed a heuristic based ranking algorithm to address these challenges. In this algorithm, the individual sensors are ranked based upon their quality of service (QoS) attributes and the resulting ranking is used by a filtering service during the sensor selection process. This information is provided to the filtering service when a sensor joins the tracking infrastructure and is subsequently only updated during idle periods, thereby, there avoiding additional overhead. We have implemented this algorithm into the existing prototypical Enhanced Distributed Object Tracking System or e-DOTS. e-DOTS has been extensively experimented with and the results of these experimentation validate the hypothesis that accurate indoor tracking can be achieved using a heterogeneous ensemble of cheap and mobile sensors. Our current investigation involves the incorporation of trust associated with sensors and deploying e-DOTS in a typical healthcare setup.Item Networked Biomedical System for Ubiquitous Health Monitoring(Hindawi, 2008-11-20) Durresi, Arjan; Durresi, Mimoza; Merkoci, Arben; Barolli, Leonard; Computer and Information Science, School of ScienceWe propose a distributed system that enables global and ubiquitous health monitoring of patients. The biomedical data will be collected by wearable health diagnostic devices, which will include various types of sensors and will be transmitted towards the corresponding Health Monitoring Centers. The permanent medical data of patients will be kept in the corresponding Home Data Bases, while the measured biomedical data will be sent to the Visitor Health Monitor Center and Visitor Data Base that serves the area of present location of the patient. By combining the measured biomedical data and the permanent medical data, Health Medical Centers will be able to coordinate the needed actions and help the local medical teams to make quickly the best decisions that could be crucial for the patient health, and that can reduce the cost of health service.Item A NEW APPROACH TO ENABLE THE BLIND PEOPLE TO “SEE”(Office of the Vice Chancellor for Research, 2011-04-08) Miranda, Jose H.Eyes are one of the most important sensors for human beings to know the world. Unfortunately, people who are blind are detached from this capability. The focus of this research is to design a device containing an imaging system for these people. This device will contain a touch-based temperature image system to represent pixels of an image. We use Light-Emitting Diode (LED) lights as sensors. Certain LED lights will be turned on with the interactions of switches and resistors to create each image. Based on the temperature that these lights distribute, the sensory array would provide a touchable image for users. In addition, throughout the project, we will maintain a focus on maximizing user friendliness.Item Poster: Infusing Trust in Indoor Tracking(ACM, 2016-06) Rybarczyk, Ryan; Raje, Rajeev; Tuceryan, Mihran; Department of Computer & Information Science, School of ScienceAn indoor tracking system is inherently an asynchronous and distributed system that contains various types (e.g., detection, selection, and fusion) of events. One of the key challenges with regards to indoor tracking is an efficient selection and arrangement of sensor devices in the environment. Selecting the "right" subset of these sensors for tracking an object as it traverses an indoor environment is the necessary precondition to achieving accurate indoor tracking. With the recent proliferation of mobile devices, specifically those with many onboard sensors, this challenge has increased in both complexity and scale. No longer can one assume that the sensor infrastructure is static, but rather indoor tracking systems must consider and properly plan for a wide variety of sensors, both static and mobile, to be present. In such a dynamic setup, sensors need to be properly selected using an opportunistic approach. This opportunistic tracking allows for a new dimension of indoor tracking that previously was often infeasible or unpractical due to logistic or financial constraints of most entities. In this paper, we are proposing a selection technique that uses trust as manifested by its a quality-of-service (QoS) feature, accuracy, in a sensor selection function. We first outline how classification of sensors is achieved in a dynamic manner and then how the accuracy can be discerned from this classification in an effort to properly identify the trust of a tracking sensor and then use this information to improve the sensor selection process. We conclude this paper with a discussion of results of this implementation on a prototype indoor tracking system in an effort to demonstrate the overall effectiveness of this selection technique.